# Generalize <a href='https://github.com/LudvigOlsen/generalize'><img src='https://raw.githubusercontent.com/LudvigOlsen/generalize/master/generalize_242x280_250dpi.png' align="right" height="140" /></a>
**Author:** [Ludvig R. Olsen](https://www.ludvigolsen.dk/) ( <r-pkgs@ludvigolsen.dk> )
The ultimate goal of training machine learning models is to generalize to new, unseen data. This package contains tools for measuring model performance across multiple datasets via cross-dataset-validation (aka. leave-one-dataset-out).
Under development!
- Not generalized enough for general usage (ironic, I know)
- Relies on an old version of scikit-learn, needs updating
- Linear regression is not currently implemented
- Help strings are likely not up-to-date
### Main functions and classes
| Function | Description |
|:-------------------------------|:-----------------------------------------------------------------------------------|
| `nested_cross_validate()` | Run (repeated) nested cross-validation. |
| `train_full_model()` | Train model on all data and save to disk. |
| `evaluate_univariate_models()` | Evaluate prediction potential of every predictor separately. |
| `PipelineDesigner` | Design a scikit-learn pipeline for use in cross-validation. |
| `ROCCurve`, `ROCCurves` | ROC curve containers with various utility methods. |
| `select_samples()` | Utility for selecting samples based on (collapsed) labels. |
Raw data
{
"_id": null,
"home_page": "https://github.com/ludvigolsen/generalize",
"name": "generalize",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.9",
"maintainer_email": null,
"keywords": null,
"author": "Ludvig Renbo Olsen",
"author_email": "mail@ludvigolsen.dk",
"download_url": "https://files.pythonhosted.org/packages/46/da/b2e9ded8defa89ebc91ee6cd7736cb1aeb59ad4dac5bc5870b06c2a785eb/generalize-0.2.1.tar.gz",
"platform": null,
"description": "# Generalize <a href='https://github.com/LudvigOlsen/generalize'><img src='https://raw.githubusercontent.com/LudvigOlsen/generalize/master/generalize_242x280_250dpi.png' align=\"right\" height=\"140\" /></a>\n\n**Author:** [Ludvig R. Olsen](https://www.ludvigolsen.dk/) ( <r-pkgs@ludvigolsen.dk> )\n\nThe ultimate goal of training machine learning models is to generalize to new, unseen data. This package contains tools for measuring model performance across multiple datasets via cross-dataset-validation (aka. leave-one-dataset-out).\n\nUnder development!\n\n - Not generalized enough for general usage (ironic, I know)\n - Relies on an old version of scikit-learn, needs updating\n - Linear regression is not currently implemented\n - Help strings are likely not up-to-date\n\n### Main functions and classes\n\n| Function | Description |\n|:-------------------------------|:-----------------------------------------------------------------------------------|\n| `nested_cross_validate()` | Run (repeated) nested cross-validation. |\n| `train_full_model()` | Train model on all data and save to disk. |\n| `evaluate_univariate_models()` | Evaluate prediction potential of every predictor separately. |\n| `PipelineDesigner` | Design a scikit-learn pipeline for use in cross-validation. |\n| `ROCCurve`, `ROCCurves` | ROC curve containers with various utility methods. |\n| `select_samples()` | Utility for selecting samples based on (collapsed) labels. |",
"bugtrack_url": null,
"license": null,
"summary": "Machine learning tools for running repeated nested leave-one-dataset-out validation and more.",
"version": "0.2.1",
"project_urls": {
"Homepage": "https://github.com/ludvigolsen/generalize",
"Repository": "https://github.com/ludvigolsen/generalize",
"issues": "https://github.com/ludvigolsen/generalize/issues"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "04c64ea3b9859d0758ab1eb9c696e982365ffb758307ae6f5b3dc12eedf863de",
"md5": "25a662006763f79008241656412fe8e0",
"sha256": "6dfc384d1e168014b750654f34c990055c7075e4d3761516a483daaca361ca35"
},
"downloads": -1,
"filename": "generalize-0.2.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "25a662006763f79008241656412fe8e0",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0,>=3.9",
"size": 150057,
"upload_time": "2024-12-05T23:15:48",
"upload_time_iso_8601": "2024-12-05T23:15:48.889647Z",
"url": "https://files.pythonhosted.org/packages/04/c6/4ea3b9859d0758ab1eb9c696e982365ffb758307ae6f5b3dc12eedf863de/generalize-0.2.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "46dab2e9ded8defa89ebc91ee6cd7736cb1aeb59ad4dac5bc5870b06c2a785eb",
"md5": "e274b06710643f7e6d6d7393ecbf270b",
"sha256": "c8ec622781cc4372450443cb7a8ed6e382e5fe27505d44cad9cabe2d3852242d"
},
"downloads": -1,
"filename": "generalize-0.2.1.tar.gz",
"has_sig": false,
"md5_digest": "e274b06710643f7e6d6d7393ecbf270b",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0,>=3.9",
"size": 121503,
"upload_time": "2024-12-05T23:15:50",
"upload_time_iso_8601": "2024-12-05T23:15:50.801717Z",
"url": "https://files.pythonhosted.org/packages/46/da/b2e9ded8defa89ebc91ee6cd7736cb1aeb59ad4dac5bc5870b06c2a785eb/generalize-0.2.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-05 23:15:50",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ludvigolsen",
"github_project": "generalize",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "generalize"
}
JSON
